Software/hardware ranking

ABSTRACT

A ranking method and system. The method includes receiving by a computing system, business requirements and associated weighting factors. The computing system receives a list of software/hardware products and associated assessment data. The business requirements are associated with product features of the software/hardware products. The computing system calculates total requirement weighting factors for the product features. The computing system stores the total requirement weighting factors.

This application is a continuation application claiming priority to Ser.No. 12/276,480, filed Nov. 24, 2008.

FIELD

The present invention relates to a method and associated system forgenerating unbiased rankings for software/hardware products.

BACKGROUND

Recommending specific items typically comprises an inefficient processwith little flexibility. Accordingly, there exists a need in the art toovercome at least some of the deficiencies and limitations describedherein above.

SUMMARY

The present invention provides a method comprising:

receiving, by a computing system from a first entity, businessrequirements data and weighting factors, wherein said businessrequirements data comprises business requirements associated asoftware/hardware solution for performing specified functions associatedwith said first entity, wherein said weighting factors are associatedwith said business requirements data, and wherein each weighting factorof said weighting factors is associated with a different businessrequirement of said business requirements;

receiving, by said computing system from a second entity, a first listof software/hardware products associated with said specified functions,wherein said first entity differs from said second entity;

receiving, by said computing system from a third entity, assessment dataassociated with said software/hardware products of said first list,wherein said assessment data comprises an assessment rating for eachsoftware/hardware product of said first list, and wherein said thirdentity differs from said second entity and said first entity;

associating, by said computing system, said business requirements andsaid weighting factors with product features of said software/hardwareproducts of said first list;

calculating, by said computing system, total requirement weightingfactors for said product features, wherein each total requirementweighting factor of said total requirement weighting factors isassociated with a different feature of said features; and

storing, by said computing system, said total requirement weightingfactors.

The present invention provides a computing system comprising a processorcoupled to a computer-readable memory unit, said memory unit comprisinginstructions that when executed by the processor implements a rankingmethod, said method comprising:

receiving, by said computing system from a first entity, businessrequirements data and weighting factors, wherein said businessrequirements data comprises business requirements associated asoftware/hardware solution for performing specified functions associatedwith said first entity, wherein said weighting factors are associatedwith said business requirements data, and wherein each weighting factorof said weighting factors is associated with a different businessrequirement of said business requirements;

receiving, by said computing system from a second entity, a first listof software/hardware products associated with said specified functions,wherein said first entity differs from said second entity;

receiving, by said computing system from a third entity, assessment dataassociated with said software/hardware products of said first list,wherein said assessment data comprises an assessment rating for eachsoftware/hardware product of said first list, and wherein said thirdentity differs from said second entity and said first entity;

associating, by said computing system, said business requirements andsaid weighting factors with product features of said software/hardwareproducts of said first list;

calculating, by said computing system, total requirement weightingfactors for said product features, wherein each total requirementweighting factor of said total requirement weighting factors isassociated with a different feature of said features; and

storing, by said computing system, said total requirement weightingfactors.

The present invention advantageously provides a simple method andassociated system capable of recommending specific items.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for generating unbiased rankings forsoftware/hardware products, in accordance with embodiments of thepresent invention.

FIG. 2 which includes FIG. 2A and FIG. 2B illustrates a flowchartdescribing an algorithm used by the system of FIG. 1 for generatingunbiased rankings for software/hardware products, in accordance withembodiments of the present invention.

FIG. 3 illustrates an example of business requirements retrieved in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 4 illustrates an example of relative weights retrieved in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 5 a illustrates an example of third party assessments retrieved inthe algorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 5 b illustrates an implementation example for executing a firststep in the algorithm of FIG. 2, in accordance with embodiments of thepresent invention.

FIG. 5 c illustrates an example for executing a second step in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 5 d illustrates an example for executing a third step in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 5 e illustrates an example for executing a fourth step in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 5 f illustrates an example for executing a fifth step in thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention.

FIG. 6 illustrates a ranking list generated by the algorithm of FIG. 2,in accordance with embodiments of the present invention.

FIG. 7 illustrates a computer apparatus used for generating unbiasedrankings for software/hardware products, in accordance with embodimentsof the present invention.

DETAILED DESCRIPTION

FIG. 1 illustrates a system 5 for generating unbiased rankings forsoftware/hardware products, in accordance with embodiments of thepresent invention. System 5 of FIG. 1 comprises a computing apparatus 8a and a computing apparatus 8 b, and a computing apparatus 8 c connectedto a computing system 10 through a network 7. Network 7 may comprise anytype of network including, inter alia, a local area network, (LAN), awide area network (WAN), the Internet, etc. Computing apparatus 8 a, 8b, and 8 c may comprise any type of computing apparatus including, interalia, a personal computer, a laptop computer, a computer terminal, etc.Computing apparatus 8 a, 8 b, and 8 c may comprise a single computingapparatus or a plurality of computing apparatuses. Computing apparatus 8a, 8 b, and 8 c is used by users from a first entity for requesting asoftware/hardware solution for performing specified functions. Computingapparatus 8 b is used by users from a second (and unrelated) entity forentering data required for providing an unbiased software/hardwaresolution for performing the specified functions. Computing apparatus 8 cis used by users from a third (and unrelated) entity for entering data(e.g., assessment data) required for providing an unbiasedsoftware/hardware solution for performing the specified functions.

Computing system 10 may comprise any type of computing system(s)including, inter alia, a personal computer (PC), a server computer, adatabase computer, etc. Computing system 10 is used to retrieve arequest for providing a software/hardware solution for performingspecified functions and generating an unbiased ranked list ofsoftware/hardware products associated with performing the specifiedfunctions. Computing system 10 comprises a memory system 14. Memorysystem 14 may comprise a single memory system. Alternatively, memorysystem 14 may comprise a plurality of memory systems. Memory system 14comprises a software application 16 and a database 12. Database 12comprises all data associated with generating the ranked list ofsoftware/hardware products. The software/hardware products may compriseany type of software and/or hardware products including, inter alia,software applications, operating systems, hardware drivers, memorydevices, microprocessors, input/output devices, video cards, dataacquisition and control systems, programmable logic controllers (PLC)etc.

Software application 16 performs a numerical comparison associated witha ‘fit’ of various software/hardware products against specified businessrequirements. The numerical comparison allows for a bias-neutralnumerical comparison of the software/hardware products (e.g., if thecompany recommending the various software/hardware products alsomanufactures some of the software/hardware products). The businessrequirements may be obtained from a first entity (e.g., a businessquestioner) through standard business analyst activities. The businessrequirements (e.g., in a list format) are then rated by importance(e.g., using ratings of high, medium, and low). The ratings may beadjusted to fit a typical bell curve. Once the requirements are rated,they are matched against a feature set comparison chart (e.g.,assessment data assessing various software/hardware products). Thecomparison chart may be created by utilizing industry accepted neutralreports such as, inter alia, the Gartner report, ECM Magic Quadrant,Forrester ECM suite comparison study, etc. The reports are used togenerate a Harvey ball chart rating each software/hardware product as a0, 0.25, 0.50, 0.75, or 1 for each feature set. The requirements arethen matched to the feature sets that cover them. Any requirements thatdo not fall any under feature sets are called out as such separately.Software application 16 calculates a sum of each requirement's weight byfeature set for each vendor (i.e., manufacturer for thesoftware/hardware products). Additionally, a sum of all feature setscores is calculated for each vendor. The aforementioned processgenerates a numerical score for assessing how well eachsoftware/hardware product's feature set meets the needs of the businessrequirements (i.e., taking into consideration the relative importance ofeach business requirement). As the requirements are ranked inconjunction with the business users and without knowledge of whatfeature sets they apply to, the possibility of bias is virtuallyeliminated.

FIG. 2 which includes FIG. 2A and FIG. 2B illustrates a flowchartdescribing an algorithm used by system 5 of FIG. 1 for generatingunbiased rankings for software/hardware products, in accordance withembodiments of the present invention. In step 201, a computing system(e.g., computing system 10 of FIG. 1) receives (i.e., from a firstentity such as a business or company) a request (e.g., via computingapparatus 8 a of FIG. 1) for providing a software/hardware solution forperforming specified functions associated with the first entity. In step202, computing system requests (i.e., in response to said requestreceived in step 201), business requirements data comprising businessrequirements associated with the specified functions of step 201. Instep 204, the computing system receives (i.e., from the first entity)the requested business requirements data. In step 206, the computingsystem receives (i.e., from said first entity) weighting factorsassociated with the business requirements data. Each weighting factor isassociated with a different business requirement of the businessrequirements. In step 207, the computing system receives (i.e., from asecond entity unrelated to the first entity) a list of software/hardwareproducts associated with performing the specified functions. In step208, the computing system receives (i.e., from a third entity or vendorunrelated to the first entity or the second entity) unbiased assessmentdata associated with the software/hardware products of the list. Theassessment data comprises an assessment rating for eachsoftware/hardware product of the list. The assessment data may bederived from any type of third party assessments such as, inter alia,the Gartner report, ECM Magic Quadrant, Forrester ECM suite comparisonstudy, etc. In step 210, the computing system associates the businessrequirements from step 204 and the weighting factors from step 206 withproduct features of the software/hardware products of list received instep 207. In step 212, the computing system calculates total requirementweighting factors for each of the product features. Each totalrequirement weighting factor may be calculated by adding groups ofweighting factors associated with each product feature. In step 215, thecomputing system calculates total feature weighting factors for thesoftware/hardware products. Each total feature weighting factor isassociated with a different software/hardware product. Each said totalfeature weighting factor is calculated by multiplying an assessmentrating for a software/hardware product with an associated totalrequirement weighting factor calculated in step 212. Each assessmentrating may be converted into a percentage value before the multiplying(i.e., before step 215 is executed). In step 216, the computing systemcalculates total feature scores for the software/hardware products. Eachtotal feature score is calculated by adding groups of the total featureweighting factors. Each said different software/hardware product isassociated with a different group. In step 220, the computing systemconverts the total feature scores into normalized scores. The totalfeature scores may be converted into normalized scores by the followingsteps:

1. Calculating a difference between an associated total feature scoreand a minimum total feature score of the total feature scores.2. Calculating a quotient by dividing the difference (i.e., from step 1)with a range of the total feature scores.3. Calculating a product by multiplying the quotient (i.e., from step 2)by four.4. Adding one to the product of step 3.

In step 224, the computing system rates or ranks (i.e., based on thenormalized scores) the software/hardware products. In step 228, thecomputing system generates (i.e., based on the ratings) a ranking listcomprising rankings for each software/hardware product. In step 232, thecomputing system stores and/or transmits the ranking list to the firstentity.

FIGS. 3-6 illustrate an example of implementation for executing thealgorithm of FIG. 2 for generating unbiased rankings forsoftware/hardware products, in accordance with embodiments of thepresent invention.

FIG. 3 illustrates a chart 300 comprising an implementation example ofbusiness requirements 302 retrieved in step 204 in the algorithm of FIG.2, in accordance with embodiments of the present invention. The businessrequirements 302 comprise identification numbers 1.0.1 . . . 1.0.9. Eachof the business requirements comprises a description 304 associated withone of identification numbers 1.0.1 . . . 1.0.9. For example,identification number 1.0.1 comprises a description 304 of “Anauthorized user shall be able to manage thousands of files and determinewhich are most current”.

FIG. 4 illustrates a chart 400 comprising an implementation example ofrelative weights 404 retrieved in step 206 in the algorithm of FIG. 2,in accordance with embodiments of the present invention. Relativeweights 404 are associated with business requirements 302. For example,business requirements 302 identification number 1.0.9 is associated witha relative weight 404 of “3” and comprises a prioritization ration 406of “Essential requirement . . . Binders”. Business management and staffpersonal may generate and associate a numerical relative weight 404 toeach of business requirements 302. The business management and staffpersonal generate numerical relative weights 404 without regard to atechnology used for a final solution thereby ensuring that theweightings are not influenced by a choice of vendors.

FIG. 5 a illustrates a chart 502 a comprising an implementation exampleof third party assessments 505 retrieved in step 208 in the algorithm ofFIG. 2, in accordance with embodiments of the present invention. Chart502 a is illustrated as a spreadsheet format. Note that any type offormat may be used. Key features 504 for software products/manufacturers508 are illustrated in the first column of chart 502 a (e.g., scanimage, Email integration, etc). Third party assessments 505 (e.g.,reports and evaluations) are utilized to rate each vendor's product. Forexample, industry reports such as, inter alia, the Forrester report orthe Gartner Group report provide unbiased evaluations of many productsand may be utilized to rate products. In the implementation exampleillustrated in FIG. 5 a, Harvey balls (i.e., illustrated as percentagevalues) are used to rate each feature for each product. A filled incircle represents 100% (i.e., a best possible score) while an emptycircle represents 0% (i.e., a worst possible score). The ratings used inthe implementation example illustrated in FIG. 5 a are 0%, 25%, 50%,75%, and 100%. For example:

1. An assessment rating for a key feature/requirement of scan image forcompany 1 software is illustrated as a full filled circle indicating anassessment rating of 100% (i.e., a best rating).2. An assessment rating for a key feature/requirement of taxonomymanagement for company 2 software is illustrated as a ¾ filled circleindicating an assessment rating of 75%.

FIG. 5 b illustrates a modified chart 502 b comprising an implementationexample of executing step 210 in the algorithm of FIG. 2, in accordancewith embodiments of the present invention. Modified chart 502 b has beenmodified from chart 502 a of FIG. 5 a. Chart 502 b comprises businessrequirements 510 associated with product key features 504. Not allbusiness requirements (e.g., business requirements 510) will be linkedor associated with each product key features 504. Therefore each ofbusiness requirements 510 should be considered equal across allvendors/manufacturers. For example, a business requirement 2.0.1 may beassociated with all the content management repositories and isconsidered to be a basic requirement that is not covered by a keyproduct feature. Since all vendors/companies support this functionality,the business requirement would have no effect on the relative scores ofthe vendors and may be left out without changing an outcome.

FIG. 5 c illustrates a modified chart 502 c comprising an implementationexample of executing step 212 in the algorithm of FIG. 2, in accordancewith embodiments of the present invention. Modified chart 502 c has beenmodified from chart 502 b of FIG. 5 b. Chart 502 c comprises a total(i.e., a sum) required weight 514 for each of key product features 504.Step 212 of FIG. 2 retrieves all requirement weights (e.g., relativeweights 404 from FIG. 4) associated with each key product feature 504and sums their values. Each total requirement weighting factor iscalculated by adding groups of weighting factors associated with eachproduct feature.

FIG. 5 d illustrates a modified chart 502 d comprising an implementationexample of executing step 215 in the algorithm of FIG. 2, in accordancewith embodiments of the present invention. Modified chart 502 d has beenmodified from chart 502 c of FIG. 5 c. Chart 502 d illustrates totalfeature weights 516. Total feature weights are calculated by multiplyinga total requirement weight 514 for each key product feature by eachvendors' score for that feature (i.e., assessment rating. Each totalfeature weight 516 is represented by a value between 0% and 100% (e.g.,illustrated as Harvey balls). The following steps describe the totalfeature weight are calculations:

1. A Harvey ball value is converted into a percent value.2. The percent value is multiplied by an associated total requirementweight 514 to arrive at a vendor's individual score for that key productfeature.

FIG. 5 e illustrates a modified chart 502 e comprising an implementationexample of executing step 216 in the algorithm of FIG. 2, in accordancewith embodiments of the present invention. Modified chart 502 e has beenmodified from chart 502 d of FIG. 5 d. Chart 502 e illustrates a sum offeature scores 522 (composite scores) for each vendor/company. Thevalues for each product feature for each vendor are summed up tocalculate each sum of feature scores 522 (composite scores) for eachvendor/company.

FIG. 5 f illustrates a modified chart 502 f comprising an implementationexample of executing step 220 in the algorithm of FIG. 2, in accordancewith embodiments of the present invention. Modified chart 502 f has beenmodified from chart 502 e of FIG. 5 e. Chart 502 f illustratesnormalized (final) scores 530 for each vendor/company. Normalized(final) scores 530 are normalized into a range between 1 and 5 for easycomparison. Sum of feature scores 522 (composite scores) may beconverted into normalized scores by the following steps:

1. Calculating a difference between an associated total feature score522 and a minimum total feature score of the total feature scores.2. Calculating a quotient by dividing the difference (i.e., from step 1)with a range of the total feature scores 532 (e.g., 70).3. Calculating a product by multiplying the quotient (i.e., from step 2)by four.4. Adding one to the product of step 3.

FIG. 6 illustrates a ranking list 601 generated in step 228 of thealgorithm of FIG. 2, in accordance with embodiments of the presentinvention. Ranking list comprises rankings for each software/hardwareproduct from each vendor/company.

FIG. 7 illustrates a computer apparatus 90 (e.g., computing system 10 ofFIG. 1) used for generating unbiased rankings for software/hardwareproducts, in accordance with embodiments of the present invention. Thecomputer system 90 comprises a processor 91, an input device 92 coupledto the processor 91, an output device 93 coupled to the processor 91,and memory devices 94 and 95 each coupled to the processor 91. The inputdevice 92 may be, inter alia, a keyboard, a software application, amouse, etc. The output device 93 may be, inter alia, a printer, aplotter, a computer screen, a magnetic tape, a removable hard disk, afloppy disk, a software application, etc. The memory devices 94 and 95may be, inter alia, a hard disk, a floppy disk, a magnetic tape, anoptical storage such as a compact disc (CD) or a digital video disc(DVD), a dynamic random access memory (DRAM), a read-only memory (ROM),etc. The memory device 95 includes a computer code 97. The computer code97 includes algorithms (e.g., the algorithm of FIG. 2) for generatingunbiased rankings for software/hardware products. The processor 91executes the computer code 97. The memory device 94 includes input data96. The input data 96 includes input required by the computer code 97.The output device 93 displays output from the computer code 97. Eitheror both memory devices 94 and 95 (or one or more additional memorydevices not shown in FIG. 7) may comprise the algorithm of FIG. 2 andmay be used as a computer usable medium (or a computer readable mediumor a program storage device) having a computer readable program codeembodied therein and/or having other data stored therein, wherein thecomputer readable program code comprises the computer code 97.Generally, a computer program product (or, alternatively, an article ofmanufacture) of the computer system 90 may comprise said computer usablemedium (or said program storage device).

Still yet, any of the components of the present invention could becreated, integrated, hosted, maintained, deployed, managed, serviced,etc. by a service provider who offers to for generate unbiased rankingsfor software/hardware products. Thus the present invention discloses aprocess for deploying, creating, integrating, hosting, maintaining,and/or integrating computing infrastructure, comprising integratingcomputer-readable code into the computer system 90, wherein the code incombination with the computer system 90 is capable of performing amethod for generating unbiased rankings for software/hardware products.In another embodiment, the invention provides a business method thatperforms the process steps of the invention on a subscription,advertising, and/or fee basis. That is, a service provider, such as aSolution Integrator, could offer to generate unbiased rankings forsoftware/hardware products. In this case, the service provider cancreate, maintain, support, etc. a computer infrastructure that performsthe process steps of the invention for one or more customers. In return,the service provider can receive payment from the customer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising content to one or morethird parties.

While FIG. 7 shows the computer system 90 as a particular configurationof hardware and software, any configuration of hardware and software, aswould be known to a person of ordinary skill in the art, may be utilizedfor the purposes stated supra in conjunction with the particularcomputer system 90 of FIG. 7. For example, the memory devices 94 and 95may be portions of a single memory device rather than separate memorydevices.

While embodiments of the present invention have been described hereinfor purposes of illustration, many modifications and changes will becomeapparent to those skilled in the art. Accordingly, the appended claimsare intended to encompass all such modifications and changes as fallwithin the true spirit and scope of this invention.

1. A method comprising: receiving, by a computing system from a firstentity, business requirements data with identification numbers andassociated descriptions and weighting factors, wherein said businessrequirements data comprises business requirements associated with asoftware/hardware solution for performing specified functions associatedwith said first entity, wherein said weighting factors are associatedwith said business requirements data, and wherein each weighting factorof said weighting factors is associated with a different businessrequirement of said business requirements; generating, by said computingsystem based on said business requirements data, a prioritization chartcomprising said business requirements associated with said weightingfactors, a prioritization rationale, and a user command description;receiving, by said computing system from a second entity, a first listof software/hardware products associated with said specified functions,wherein said first entity differs from said second entity; receiving, bysaid computing system from a third entity, assessment data associatedwith said software/hardware products of said first list, wherein saidassessment data comprises an assessment rating for eachsoftware/hardware product of said first list, wherein said assessmentdata comprises key product features for each software/hardware productand software products manufacturers of said first list, and wherein saidthird entity differs from said second entity and said first entity;generating, by said computing system, a first chart comprising said keyproduct features with respect to said software products manufacturersand percentage values representing ratings for said key productfeatures; calculating, by said computing system, total requirementweighting factors for said product features, wherein each totalrequirement weighting factor of said total requirement weighting factorsis associated with a different feature of said key product features;generating, by said computing system, a second chart comprising said keyproduct features with respect to said software products manufacturers,said percentage values, said total requirement weighting factors, andnumerical representations of said business requirements; calculating, bysaid computing system, total feature weighting factors for saidsoftware/hardware products, wherein each total feature weighting factorof said total feature weighting factors is associated with a differentsoftware/hardware product of said software/hardware products, andwherein each said total feature weighting factor is based on a functionof each said assessment rating and an associated total requirementweighting factor of said total requirement weighting factors;generating, by said computing system, a third chart comprising amodified version of said second chart, wherein said third chartcomprises said total feature weighting factors associated with each ofsaid key product features and each of said percentage values;calculating, by said computing system, total feature scores for saidsoftware/hardware products, wherein each total feature score of saidtotal feature scores is calculated by adding groups of said totalfeature weighting factors, and wherein each said differentsoftware/hardware product is associated with a different group of saidgroups; calculating, by said computing system, normalized scoresassociated with each total feature score of said total feature scores,wherein said calculating each normalized score of said normalized scorescomprises: calculating a difference between said each total featurescore of said total feature scores and a minimum total feature score ofsaid total feature scores; calculating a quotient by dividing saiddifference with a range of said total feature scores; calculating aproduct by multiplying said quotient by four; and adding one to saidproduct; rating, by said computing system based on said normalizedscores, said software/hardware products; generating, by said computingsystem, a fourth chart comprising a modified version of said thirdchart, wherein said fourth chart comprises, said total feature weightingfactors associated with each of said key product features, each of saidpercentage values, and said normalized scores; generating, by saidcomputing system based on said rating, a ranking list comprisingrankings for each said software/hardware product of saidsoftware/hardware products associated with said normalized scores; andtransmitting, by said computing system to said first entity, saidranking list.
 2. The method of claim 1, wherein said calculating eachsaid total feature weighting factor comprises multiplying each saidassessment rating with said associated total requirement weightingfactor of said total requirement weighting factors.
 3. The method ofclaim 2, wherein each said assessment rating is converted into apercentage value before said multiplying.
 4. The method of claim 1,further comprising: presenting, by said computing system to said secondentity in a spreadsheet format, said business requirements data, saidweighting factors, said first list of software/hardware products, saidassessment data, said total requirement weighting factors, said totalfeatures weighting factors, said total feature scores, and saidnormalized scores.
 5. The method of claim 1, wherein said businessrequirements are associated with said first entity.
 6. The method ofclaim 1, wherein said weighting factors are not associated with saidsoftware/hardware products of said first list.
 7. The method of claim 1,further comprising: presenting, by said computing system to said secondentity, each said assessment rating for each software/hardware productof said first list, wherein each said assessment rating is presented asa Harvey ball chart.
 8. The method of claim 1, wherein each said totalrequirement weighting factor of said total requirement weighting factorsis calculated by adding a group of weighting factors of said weightingfactors, and wherein each said group of weighting factors is associatedwith an associated feature of said features.
 9. A process for supportingcomputing infrastructure, said process comprising providing at least onesupport service for at least one of creating, integrating, hosting,maintaining, and deploying computer-readable code in a computer systemcomprising a computer processor, wherein said computer processor, inresponse to said providing, carries out instructions contained in saidcode causing said computer system to perform a method comprising:receiving, by said computing system from a first entity, businessrequirements data with identification numbers and associateddescriptions and weighting factors, wherein said business requirementsdata comprises business requirements associated with a software/hardwaresolution for performing specified functions associated with said firstentity, wherein said weighting factors are associated with said businessrequirements data, and wherein each weighting factor of said weightingfactors is associated with a different business requirement of saidbusiness; generating, by said computing system based on said businessrequirements data, a prioritization chart comprising said businessrequirements associated with said weighting factors, a prioritizationrationale, and a user command description; receiving, by said computingsystem from a second entity, a first list of software/hardware productsassociated with said specified functions, wherein said first entitydiffers from said second entity; receiving, by said computing systemfrom a third entity, assessment data associated with saidsoftware/hardware products of said first list, wherein said assessmentdata comprises an assessment rating for each software/hardware productof said first list, wherein said assessment data comprises key productfeatures for each software/hardware product and software productsmanufacturers of said first list, and wherein said third entity differsfrom said second entity and said first entity; generating, by saidcomputing system, a first chart comprising said key product featureswith respect to said software products manufacturers and percentagevalues representing ratings for said key product features; calculating,by said computing system, total requirement weighting factors for saidproduct features, wherein each total requirement weighting factor ofsaid total requirement weighting factors is associated with a differentfeature of said key product features; generating, by said computingsystem, a second chart comprising said key product features with respectto said software products manufacturers, said percentage values, saidtotal requirement weighting factors, and numerical representations ofsaid business requirements; calculating, by said computing system, totalfeature weighting factors for said software/hardware products, whereineach total feature weighting factor of said total feature weightingfactors is associated with a different software/hardware product of saidsoftware/hardware products, and wherein each said total featureweighting factor is based on a function of each said assessment ratingand an associated total requirement weighting factor of said totalrequirement weighting factors; generating, by said computing system, athird chart comprising a modified version of said second chart, whereinsaid third chart comprises said total feature weighting factorsassociated with each of said key product features and each of saidpercentage values; calculating, by said computing system, total featurescores for said software/hardware products, wherein each total featurescore of said total feature scores is calculated by adding groups ofsaid total feature weighting factors, and wherein each said differentsoftware/hardware product is associated with a different group of saidgroups; calculating, by said computing system, normalized scoresassociated with each total feature score of said total feature scores,wherein said calculating each normalized score of said normalized scorescomprises: calculating a difference between said each total featurescore of said total feature scores and a minimum total feature score ofsaid total feature scores; calculating a quotient by dividing saiddifference with a range of said total feature scores; calculating aproduct by multiplying said quotient by four; and adding one to saidproduct; rating, by said computing system based on said normalizedscores, said software/hardware products; generating, by said computingsystem, a fourth chart comprising a modified version of said thirdchart, wherein said fourth chart comprises, said total feature weightingfactors associated with each of said key product features, each of saidpercentage values, and said normalized scores; generating, by saidcomputing system based on said rating, a ranking list comprisingrankings for each said software/hardware product of saidsoftware/hardware products associated with said normalized scores; andtransmitting, by said computing system to said first entity, saidranking list.
 10. A computer program product, comprising a computerreadable storage device storing a computer readable program code, saidcomputer readable program code comprising an algorithm that whenexecuted by a computer processor of a computing system implements amethod, said method comprising: receiving, by said computing system froma first entity, business requirements data with identification numbersand associated descriptions and weighting factors, wherein said businessrequirements data comprises business requirements associated with asoftware/hardware solution for performing specified functions associatedwith said first entity, wherein said weighting factors are associatedwith said business requirements data, and wherein each weighting factorof said weighting factors is associated with a different businessrequirement of said business requirements; generating, by said computingsystem based on said business requirements data, a prioritization chartcomprising said business requirements associated with said weightingfactors, a prioritization rationale, and a user command description;receiving, by said computing system from a second entity, a first listof software/hardware products associated with said specified functions,wherein said first entity differs from said second entity; receiving, bysaid computing system from a third entity, assessment data associatedwith said software/hardware products of said first list, wherein saidassessment data comprises an assessment rating for eachsoftware/hardware product of said first list, wherein said assessmentdata comprises key product features for each software/hardware productand software products manufacturers of said first list, and wherein saidthird entity differs from said second entity and said first entity;generating, by said computing system, a first chart comprising said keyproduct features with respect to said software products manufacturersand percentage values representing ratings for said key productfeatures; calculating, by said computing system, total requirementweighting factors for said product features, wherein each totalrequirement weighting factor of said total requirement weighting factorsis associated with a different feature of said key product features;generating, by said computing system, a second chart comprising said keyproduct features with respect to said software products manufacturers,said percentage values, said total requirement weighting factors, andnumerical representations of said business requirements; calculating, bysaid computing system, total feature weighting factors for saidsoftware/hardware products, wherein each total feature weighting factorof said total feature weighting factors is associated with a differentsoftware/hardware product of said software/hardware products, andwherein each said total feature weighting factor is based on a functionof each said assessment rating and an associated total requirementweighting factor of said total requirement weighting factors;generating, by said computing system, a third chart comprising amodified version of said second chart, wherein said third chartcomprises said total feature weighting factors associated with each ofsaid key product features and each of said percentage values;calculating, by said computing system, total feature scores for saidsoftware/hardware products, wherein each total feature score of saidtotal feature scores is calculated by adding groups of said totalfeature weighting factors, and wherein each said differentsoftware/hardware product is associated with a different group of saidgroups; calculating, by said computing system, normalized scoresassociated with each total feature score of said total feature scores,wherein said calculating each normalized score of said normalized scorescomprises: calculating a difference between said each total featurescore of said total feature scores and a minimum total feature score ofsaid total feature scores; calculating a quotient by dividing saiddifference with a range of said total feature scores; calculating aproduct by multiplying said quotient by four; and adding one to saidproduct; rating, by said computing system based on said normalizedscores, said software/hardware products; generating, by said computingsystem, a fourth chart comprising a modified version of said thirdchart, wherein said fourth chart comprises, said total feature weightingfactors associated with each of said key product features, each of saidpercentage values, and said normalized scores; generating, by saidcomputing system based on said rating, a ranking list comprisingrankings for each said software/hardware product of saidsoftware/hardware products associated with said normalized scores; andtransmitting, by said computing system to said first entity, saidranking list.
 11. A computing system comprising a processor coupled to acomputer-readable memory unit, said memory unit comprising instructionsthat when executed by the processor implements a ranking method, saidmethod comprising: receiving, by said computing system from a firstentity, business requirements data with identification numbers andassociated descriptions and weighting factors, wherein said businessrequirements data comprises business requirements associated asoftware/hardware solution for performing specified functions associatedwith said first entity, wherein said weighting factors are associatedwith said business requirements data, and wherein each weighting factorof said weighting factors is associated with a different businessrequirement of said business requirements; generating, by said computingsystem based on said business requirements data, a prioritization chartcomprising said business requirements associated with said weightingfactors, a prioritization rationale, and a user command description;receiving, by said computing system from a second entity, a first listof software/hardware products associated with said specified functions,wherein said first entity differs from said second entity; receiving, bysaid computing system from a third entity, assessment data associatedwith said software/hardware products of said first list, wherein saidassessment data comprises an assessment rating for eachsoftware/hardware product of said first list, wherein said assessmentdata comprises key product features for each software/hardware productand software products manufacturers of said first list, and wherein saidthird entity differs from said second entity and said first entity;generating, by said computing system, a first chart comprising said keyproduct features with respect to said software products manufacturersand percentage values representing ratings for said key productfeatures; calculating, by said computing system, total requirementweighting factors for said product features, wherein each totalrequirement weighting factor of said total requirement weighting factorsis associated with a different feature of said key product features;generating, by said computing system, a second chart comprising said keyproduct features with respect to said software products manufacturers,said percentage values, said total requirement weighting factors, andnumerical representations of said business requirements; calculating, bysaid computing system, total feature weighting factors for saidsoftware/hardware products, wherein each total feature weighting factorof said total feature weighting factors is associated with a differentsoftware/hardware product of said software/hardware products, andwherein each said total feature weighting factor is based on a functionof each said assessment rating and an associated total requirementweighting factor of said total requirement weighting factors;generating, by said computing system, a third chart comprising amodified version of said second chart, wherein said third chartcomprises said total feature weighting factors associated with each ofsaid key product features and each of said percentage values;calculating, by said computing system, total feature scores for saidsoftware/hardware products, wherein each total feature score of saidtotal feature scores is calculated by adding groups of said totalfeature weighting factors, and wherein each said differentsoftware/hardware product is associated with a different group of saidgroups; calculating, by said computing system, normalized scoresassociated with each total feature score of said total feature scores,wherein said calculating each normalized score of said normalized scorescomprises: calculating a difference between said each total featurescore of said total feature scores and a minimum total feature score ofsaid total feature scores; calculating a quotient by dividing saiddifference with a range of said total feature scores; calculating aproduct by multiplying said quotient by four; and adding one to saidproduct; rating, by said computing system based on said normalizedscores, said software/hardware products; generating, by said computingsystem, a fourth chart comprising a modified version of said thirdchart, wherein said fourth chart comprises, said total feature weightingfactors associated with each of said key product features, each of saidpercentage values, and said normalized scores; generating, by saidcomputing system based on said rating, a ranking list comprisingrankings for each said software/hardware product of saidsoftware/hardware products associated with said normalized scores; andtransmitting, by said computing system to said first entity, saidranking list.
 12. The computing system of claim 11, wherein saidcalculating each said total feature weighting factor comprisesmultiplying each said assessment rating with said associated totalrequirement weighting factor of said total requirement weightingfactors.
 13. The computing system of claim 12, wherein each saidassessment rating is converted into a percentage value before saidmultiplying.
 14. The computing system of claim 11, wherein said businessrequirements are associated with said first entity.
 15. The computingsystem of claim 11, wherein said weighting factors are not associatedwith said software/hardware products of said first list.
 16. Thecomputing system of claim 11, wherein said method further comprises:presenting, by said computing system to said second entity, each saidassessment rating for each software/hardware product of said first list,wherein each said assessment rating is presented as a Harvey ball chart.